CN112017739A

CN112017739A - Method and system for automatically checking new hospital infection in specific time period

Info

Publication number: CN112017739A
Application number: CN202010641711.2A
Authority: CN
Inventors: 林�建; 霍瑞; 陈春平
Original assignee: Hangzhou Xinglin Information Technology Co ltd
Current assignee: Hangzhou Xinglin Information Technology Co ltd
Priority date: 2020-07-06
Filing date: 2020-07-06
Publication date: 2020-12-01

Abstract

The invention provides a method and a system for automatically checking the leakage of newly-released hospital infection in a specific time period. According to the clinical report content of the infection information, the infection diagnosis information which is required to be reported by a clinician before the patient is discharged and is not reported is obtained through screening, the automatic leakage check of the newly released hospital infection in a specific time period is realized, and the number of the hospital infection which is reported in a missing mode can be automatically obtained and output. The invention can automatically check the hospital infection and has high check accuracy.

Description

Method and system for automatically checking new hospital infection in specific time period

Technical Field

The invention belongs to the technical field of hospital infection management, and particularly relates to a method and a system for automatically checking the leakage of newly-released hospital infection in a specific time period.

Background

Nosocomial infections refer to infections acquired by hospitalized patients in the hospital, including both infections occurring during hospitalization and infections occurring after discharge; nosocomial infections fall into two categories: the first is exogenous infection, also called cross infection, which refers to infection that a patient or a worker receives in a hospital through daily diagnosis and treatment activities, contact between the patient and the patient or from a polluted environment, such as infection which is not endurable in operation; the other is endogenous infection, also called self-infection, which is the infection caused by the disturbance of normal flora in vivo, the activation of potential pathogenic bacteria in vivo, the displacement of resident microorganisms originally existing in the body cavity or body surface of a patient and the like in the process of receiving diagnosis and treatment because the resistance of the body of the patient is reduced due to diseases.

The new cases of missed reports of nosocomial infections in a specific period refer to confirmed cases of nosocomial infections that should be reported but not reported by the same new clinician among all hospitalized patients in the specific period or that should be diagnosed. Nosocomial infection cases that should be reported but not reported include: cases that the clinician has made a diagnosis of a nosocomial infection but not reported, cases that should be diagnosed by a nosocomial infection but not diagnosed by the clinician, are found by professional monitoring. The statistics and reporting of hospital infection have great guiding significance for prevention, control and treatment of diseases, so that a hospital infection system generally performs statistics and management on hospital infection, however, the conventional hospital infection statistics generally performs statistics on reported confirmed infection cases, but cannot effectively manage hospital infection which is not reported, so that the problem of wrong management of hospital infection information is caused, and important hospital infection information is easily missed.

The invention patent application with the publication number of CN 106250668A discloses a system and a method for preventing and reporting legal infectious diseases such as hand-foot-and-mouth disease influenza and the like, and the system comprises three functional modules, namely automatic information acquisition, automatic interception report of the legal infectious diseases and automatic leakage check and reporting of the legal infectious diseases. The infectious disease anti-missing report management method is determined by foot mouth disease, influenza and other methods, and comprises the following steps: automatic information acquisition, including outpatient log registration, formation of legal infectious disease electronic report card, legal infectious disease report card, hospital entry and exit registration and abnormal inspection result registration; and the hospital HIS system is called by using the outpatient service log registration module to form an electronic outpatient service log, and the data acquisition sources comprise information of a registration place in the HIS system, information of an outpatient service doctor workstation, information of an outpatient service electronic medical record, information of an electronic medical record in a department of housing, and the like.

Although the above application mentions the implementation of automatic false positive detection of legal infectious diseases, no specific false positive detection method is described. Moreover, the nosocomial HIS system is automatically screened for the legal infectious diseases, all cases diagnosed as the legal infectious diseases are automatically screened out through ICDlO codes, and the sensing diseases between the hospitalization period and the outside of the hospitalization period cannot be effectively distinguished, so that the infection of a new hospital cannot be accurately checked. Therefore, how to realize automatic leak detection of new hospital infection in a specific time period is a problem to be solved urgently in the field.

Disclosure of Invention

The invention aims to provide a method and a system for automatically checking the leakage of newly-sent nosocomial infection in a specific time period, aiming at the defects of the prior art. The invention can realize automatic leak detection of newly-released hospital infection in a specific time period, and can automatically acquire and output the number of hospital infection missed reports. The invention can automatically check the hospital infection and has high check accuracy.

In order to achieve the purpose, the invention adopts the following technical scheme:

a method for automatic leak detection of newly-released hospital infections at a particular time period, comprising the steps of:

s1, receiving the statistical time and department selected by the user, and determining the authority department of the user according to the identity information of the user;

s2, collecting the patient' S information B of the department transfer, judging whether there is a record of the department transfer that the time and the statistical time are crossed, and the department belongs to the authority department and the selected department at the same time in the information B of the department transfer, if so, executing step S3, if not, outputting the number of missed hospital infection as 0;

s3, acquiring hospitalization process information A of the patient, and acquiring the hospitalization time and the discharge time of the patient based on the hospitalization process information, wherein the hospitalization time and the discharge time are jointly used as parameters g.MC2;

s4, acquiring infection information H of a patient, and dividing the infection information H into infection information H (a) Y confirmed by a user and infection information H (a) N not confirmed by examination;

s5, acquiring infection information in the infection information h (a) Y that is surgical site-independent, infected in hospital and infected at time during patient hospitalization based on the parameter g.mc2;

s6, screening the infection information H (d) Y based on the statistical time, the authority department and the selected department to obtain the infection information H (g) Y of the non-operation part infection;

s7, acquiring surgical information G of the patient, and acquiring surgical information G (a) _ Y performed in the time range of patient admission and discharge in the surgical information G based on the parameter g.MC2;

s8, screening the operation information G (a) _ Y based on the statistical time, the authority department and the selected department to obtain screened operation information G (d) _ Y;

s9, acquiring infection case identification g.8QR in the operation information G (d) Y, and acquiring infection information H (b1) Y of operation site infection based on the infection information H (a) Y and the infection case identification g.8QR;

s10, combining the infection information H (g) Y of the non-surgical site infection and the infection information H (b1) Y of the surgical site infection to obtain infection diagnosis information H (H);

s11, acquiring discharge time g.3cn in the hospitalization procedure information a, and acquiring infection diagnostic information h (i) _ Y generated before discharge of the patient in the infection diagnostic information h (h) based on the discharge time g.3cn;

and S12, acquiring the infection diagnosis information H (j) Y which is not reported by the clinician before the patient is discharged from the hospital in the infection diagnosis information H (i) Y based on the clinical report content, and outputting the number of missed hospital infections based on the number recorded in the infection diagnosis information H (j) Y.

Further, the step S2 specifically includes:

s21, collecting the patient' S information B of the branch department, dividing the information B of the branch department into information B (a) and Y of the branch department whose time is crossed with the statistical time and information B (a) and N of the branch department whose time is not crossed with the statistical time;

s22, dividing the branch information B (a) _ Y into branch information B (b) _ Y of which the department belongs to the authority department and branch information B (b) _ N of which the department does not belong to the authority department based on the authority department;

s23, dividing the branch information B (b) _ Y into branch information B (c) _ Y of which the department belongs to the selected department and branch information B (c) _ N of which the department does not belong to the selected department based on the selected department;

s24, judging whether the branch information B (c) and Y (Y) has branch records, if yes, executing step S3, and if not, outputting the number of missed hospital infection as 0.

Further, the step S5 specifically includes:

s51, dividing the infection information H (a) Y into infection information H (b) Y irrelevant to the operation position and infection information H (b) N relevant to the operation position infection;

s52, dividing the infection information H (b) Y into nosocomial infection information H (c) Y and extramural infection information H (c) N;

s53, dividing the infection information h (c) Y into infection information h (d) Y with an infection time during patient hospitalization and infection information h (d) N with an infection time during patient hospitalization based on the parameter g.mc2.

Further, the step S6 specifically includes:

s61, dividing the infection information H (d) Y into infection information H (e) Y with infection time within the statistical time range and infection information H (e) N without infection time within the statistical time range;

s62, dividing the infection information H (e) _ Y into infection information H (f) _ Y of which department belongs to the authority department and infection information H (f) _ N of which department does not belong to the authority department based on the authority department;

s63, based on the selected department, dividing the infection information H (f) Y into infection information H (g) Y of which the department belongs to the selected department and infection information H (g) N of which the department does not belong to the selected department, and using the infection information H (g) Y as the infection information of the non-operation part.

Further, the step S8 specifically includes:

s81, dividing the operation information G (a) Y into operation information G (b) Y within the statistical time range and operation information G (b) N not within the statistical time range;

s82, dividing the operation information G (b) _ Y into operation information G (c) _ Y of which the department belongs to the authority department and operation information G (c) _ N of which the department does not belong to the authority department based on the authority department;

s83, based on the selected department, dividing the operation information G (c) _ Y into operation information G (d) _ Y of which the department belongs to the selected department and operation information G (d) _ N of which the department does not belong to the selected department.

The invention also provides a system for automatically checking the leakage of newly-released hospital infection in a specific time period, which comprises the following steps:

the receiving module is used for receiving the statistical time and department selected by the user and determining the authority department of the user according to the identity information of the user;

the collection and judgment module is used for collecting the patient' S branch information B, judging whether the branch information B has a branch record that the time is crossed with the statistical time and the departments belong to the authority department and the selected department at the same time, if so, executing the step S3, and if not, outputting the number of missed hospital infection as 0;

the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring hospitalization process information A of a patient, acquiring the hospitalization time and the discharge time of the patient based on the hospitalization process information, and taking the hospitalization time and the discharge time as parameters g.MC2;

the first infection information dividing module is used for collecting infection information H of a patient, and dividing the infection information H into infection information H (a) Y confirmed by a user and infection information H (a) N not confirmed by examination;

an infection information partitioning module for obtaining infection information of the infection information h (a) Y that is surgical site-independent, infected in a hospital and has an infection time during hospitalization of a patient, based on the parameter g.mc2;

the non-surgical site infection information determining module is used for screening the infection information H (d) _ Y based on the statistical time, the authority department and the selected department to obtain the infection information H (g) _ Y of the non-surgical site infection;

the second acquisition module is used for acquiring surgical information G of the patient and acquiring surgical information G (a) _ Y which is performed in the hospital admission and discharge time range of the patient in the surgical information G based on the parameter g.MC2;

the operation information dividing module is used for screening the operation information G (a) _ Y based on the statistical time, the authority department and the selected department to obtain the screened operation information G (d) _ Y;

a surgical site infection information determination module, configured to acquire infection case identifier g.8qr in the surgical information g (d) Y, and obtain infection information H (b1) _ Y of surgical site infection based on the infection information H (a) Y and the infection case identifier g.8qr;

an infection diagnosis information determining module for merging the infection information H (g) _ Y of the non-surgical site infection and the infection information H (b1) _ Y of the surgical site infection to obtain infection diagnosis information H (H);

an infection diagnosis information dividing module for acquiring discharge time g.3cn in hospitalization process information a, and acquiring infection diagnosis information h (i) _ Y generated before discharge of the patient in the infection diagnosis information h (h) based on the discharge time g.3cn;

and the missed-report hospital infection determining module is used for acquiring infection diagnosis information H (j) Y which is not reported by a clinician before the patient is discharged from the hospital in the infection diagnosis information H (i) Y based on the clinical report content, and outputting the number of missed-report hospital infections based on the number of the infection diagnosis information H (j) Y.

Further, the collecting and judging module specifically includes:

the first division module of the information of the branch department, is used for gathering the information B of the branch department of the patient, divide the information B of the branch department into the information B (a) Y of the branch department that there is intersection with the said statistical time of time and information B (a) N of the branch department that the time does not intersect with the said statistical time;

the department information second division module is used for dividing the department information B (a) _ Y into department information B (b) _ Y of which the department belongs to the authority department and department information B (b) _ N of which the department does not belong to the authority department based on the authority department;

the third division module of the department information is used for dividing the department information B (b) _ Y into the department information B (c) _ Y of which the department belongs to the selected department and the department information B (c) _ N of which the department does not belong to the selected department based on the selected department;

and the judging module is used for judging whether the branch information B (c) and Y (Y) has a branch record, if so, executing the step S3, and if not, outputting the number of the missed hospital infection as 0.

Further, the infection information partitioning module specifically includes:

an infection information second division module for dividing the infection information h (a) Y into infection information h (b) Y unrelated to the surgical site and infection information h (b) N related to the surgical site infection;

the infection information third dividing module is used for dividing the infection information H (b) Y into infection information H (c) Y of nosocomial infection and infection information H (c) N of nosocomial infection;

and the infection information fourth dividing module is used for dividing the infection information H (c) Y into the infection information H (d) Y with the infection time during the hospitalization of the patient and the infection information H (d) N with the infection time not during the hospitalization of the patient based on the parameter g.MC2.

Further, the non-surgical site infection information determination module specifically includes:

the infection information fifth dividing module is used for dividing the infection information H (d) Y into infection information H (e) Y with infection time within the range of statistical time period and infection information H (e) N without infection time within the range of statistical time period;

the infection information sixth dividing module is used for dividing the infection information H (e) _ Y into infection information H (f) _ Y of which departments belong to the authority department and infection information H (f) _ N of which departments do not belong to the authority department based on the authority department;

and the infection information seventh dividing module is used for dividing the infection information H (f) _ Y into the infection information H (g) _ Y of which the department belongs to the selected department and the infection information H (g) _ N of which the department does not belong to the selected department based on the selected department, and taking the infection information H (g) _ Y as the infection information infected by the non-surgical part.

Further, the operation information dividing module specifically includes:

the first division module of the operation information is used for dividing the operation information G (a) _ Y into operation information G (b) _ Y in the range of statistical time period and operation information G (b) _ N not in the range of statistical time period;

the operation information second division module is used for dividing the operation information G (b) _ Y into operation information G (c) _ Y of which the department belongs to the authority department and operation information G (c) _ N of which the department does not belong to the authority department based on the authority department;

and the operation information third dividing module is used for dividing the operation information G (c) _ Y into operation information G (d) _ Y of which the department belongs to the selected department and operation information G (d) _ N of which the department does not belong to the selected department based on the selected department.

The invention describes a specific implementation mode of automatic leak detection of hospital infection in detail, and utilizes the information of branch departments, the information of hospitalization process, the infection information, the operation information, the selected statistical time, the department and the authority department of the user determined according to the identity information of the user to realize the automatic leak detection of newly issued hospital infection in a specific period, and simultaneously can automatically acquire and output the number of missed hospital infection. The invention can automatically check the hospital infection, avoids the labor intensity of manual data statistics, and simultaneously realizes the automatic supervision of the hospital infection information by automatically checking the new hospital infection. The invention effectively distinguishes the hospitalization period from the hospitalization external sensing diseases, can accurately search the new reported cases of the hospital, simultaneously fully utilizes the information of the department transfer, the hospitalization process, the infection information and the operation information, finely analyzes the relevant data of the infection information, accurately determines the new reported cases of the hospital infection, and has high leak detection accuracy.

Drawings

FIG. 1 is a flowchart of a method for automatically detecting new hospital infection during a specific period, according to an embodiment;

fig. 2 is a structural diagram of a system for automatically checking the leakage of newly-sent nosocomial infections in a specific period according to the second embodiment.

Detailed Description

The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.

It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.

The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.

In the following examples, X (y) type specification:

x represents a data set of a certain type;

y represents a serial number used for distinguishing a front data set and a rear data set of the same type of data in different logic units;

x (y) represents a data set under different logical units for a certain type of data;

y represents a coincidence condition;

n represents nonconforming;

example one

As shown in fig. 1, the present embodiment proposes a method for automatically checking for new hospital infection in a specific period, which includes:

the automatic leakage check of new hospital infection is carried out, and the times of the reported cases of the corresponding infection need to be counted. The new hospital infection of missing reports needs to meet the following requirements: 1. the patient's stay in the hospital is within the statistical time frame. That is, the time period formed by the admission time and the discharge time of the patient is crossed with the statistical time; 2. patients had nosocomial infections and the time of infection was between the hospitalization period and the statistical time. Wherein the infection time of the surgical site infection is calculated as the surgical start time; 3. the hospital infection cases of the patients are not reported or reported in time by doctors, and the reported cases comprise the following three conditions: in hospital infection cases, the clinician did not report hospital infection cases; nosocomial infection cases excluded by clinicians; the clinician confirms the case of nosocomial infection after patient discharge; 4. and the requirement of user options is met.

Therefore, the invention is used for automatically checking the leakage of the new hospital infection in a specific time period, and therefore, a user is required to select a corresponding time period, namely the user selects corresponding statistical time to count and search the new hospital infection in the statistical time. In addition, for hospital infection, a user usually checks the infection of a specific department, so that the invention also sets a corresponding department besides counting time. The hospital data has corresponding privacy, so that the statistics and the omission of the hospital data require a user to acquire corresponding data authority. The data authority of the user is associated with the corresponding identity information, so that the authority department of the user is determined according to the identity information of the operation user, and the data in the authority department is checked for omission and counted.

the branch information is used for recording the information of entering and leaving the department of each diagnosis and treatment department during the hospitalization period of the patient, and specifically comprises the patient case number, the department, the time of entering the department, the time of leaving the department and the like. For the branch information B, the invention firstly screens the branch information based on statistical time, authority departments and selected departments, and the missed new hospital infection is possible to exist only if the corresponding branch records exist after screening. Therefore, when there is no branch record after screening, that is, there is no case of meeting the requirements of statistical time, authority department and selected department at the same time, the number of hospital infection missed reports is 0, that is, there is no case of missed reports of new hospital infection. The invention screens the branch information in sequence based on the statistical time, the authority department and the selected department, therefore, the step S2 specifically comprises:

the invention firstly screens the information B of the department transfer based on the statistical time, wherein the information B is the initial data set of the type of the department transfer of the corresponding patient. Y represents a qualified branch record, and N represents an unqualified branch record.

For example, the referral information B is:

patient's case number	Department's office	Time of entering the clinic	Time of delivery
				123456(1)	Neurology department	2019-01-01 00:00:12	2019-01-05 01:00:12
123456(1)	ICU	2019-01-05 01:00:12	2019-01-08 02:00:12
				123456(1)	Rehabilitation department	2019-01-08 02:00:12	2019-01-12 03:00:12

The statistical time is as follows: 2019-01-0600: 00:00 to 2019-01-2023:59:59, then B (a) Y is:

patient's case number	Department's office	Time of entering the clinic	Time of delivery
				123456(1)	ICU	2019-01-05 01:00:12	2019-01-08 02:00:12
123456(1)	Rehabilitation department	2019-01-08 02:00:12	2019-01-12 03:00:12

B (a) N is:

patient's case number	Department's office	Time of entering the clinic	Time of delivery
				123456(1)	Neurology department	2019-01-01 00:00:12	2019-01-05 01:00:12

because the authority of each user is different, the invention screens the branch information B (a) Y based on the authority department room, so that the data operated by the user is adaptive to the corresponding authority. Incidentally, the branch information b (b) _ Y is a branch record in a department belonging to the authority range managed by the user, and the branch information b (b) _ N is a branch record in a department not belonging to the authority range managed by the user.

For example, the rights department is: all departments, for the above b (a) _ Y, b (b) _ Y:

B (b) N is:

patient's case number

Department's office

Time of entering the clinic

Time of delivery

in the invention, the user can check the missed infection of the new issue hospital aiming at a specific department, therefore, the invention screens the department information B (b) _ Y based on the selected department, so that the statistical and screened data is adaptive to the department selected by the user independently, and the user can select the corresponding data according to the requirement to count the missed report cases of the specific department.

For example, the department selected by the user is ICU, and for b (b) _ Y, b (c) _ Y described above:

patient's case number	Department's office	Time of entering the clinic	Time of delivery
				123456(1)	ICU	2019-01-05 01:00:12	2019-01-08 02:00:12

B (c) N is:

patient's case number	Department's office	Time of entering the clinic	Time of delivery
				123456(1)	Rehabilitation department	2019-01-08 02:00:12	2019-01-12 03:00:12

Specifically, the invention judges according to the branch records B (c) _ Y, if the patient has records after the three steps, the operation is continued downwards, if the patient has no records, the operation is ended, and the result is 0.

the hospitalization process information is used for integrally recording the hospitalization process of the patient, and specifically comprises the patient case number, the hospital admission department, the hospital admission time, the hospital discharge department and the hospital discharge time. The method comprises the steps of firstly obtaining the hospitalization process information A of a patient, and further obtaining the relevant information of the fields of the admission time and the discharge time, wherein the relevant information is jointly used as the parameter g.MC2.

For example, hospitalization procedure information a is:

patient's case number	Admission department	Time of admission	Discharge department	Time of discharge
					123456(1)	Neurology department	2019-01-01 00:00:12	Rehabilitation department	2019-01-12 03:00:12

The obtained parameter g.mc2 is: [2019-01-0100:00:12,2019-01-1203:00:12].

the infection information is used for recording all specific infection conditions of the patient, and specifically comprises the patient case number, an infection department, infection time, an infection part, operation time, state, infection type, infection case identification, clinical report time, clinical report content and early warning time corresponding to the infection. Since there is some non-approved data in the infection information that does not need to be statistically filtered first. Therefore, the present invention first screens the acquired infection information H to select infection information that has been confirmed by the user.

Specifically, the invention firstly screens and divides the infection information H based on a 'status' field in the infection information, wherein the status field is 'confirmed', which indicates that the infection record has been confirmed by a user, and when the status field is 'excluded', which indicates that the infection record has not been checked and confirmed.

For example, the infection information H collected is:

then H (a) _ Y is:

h (a) N is:

in the present invention, the acquired infection information h (a) Y is screened to select infection information that is not related to the surgical site, is infected in a hospital, and has an infection time during which the patient is hospitalized, and therefore, step S5 specifically includes:

because the infection time of the operation position is calculated by the operation starting time causing the infection, the invention screens and divides the infection information H (a) Y based on the field of 'infection corresponding operation time' in the infection information, when the field of 'infection corresponding operation time' comprises corresponding operation time information, the infection record is related to the operation position infection, and when the field of 'infection corresponding operation time' does not comprise corresponding operation time information, the infection record is unrelated to the operation position.

For H (a) Y, H (b) Y mentioned above:

h (b) N is:

the infection information includes nosocomial and extramural infection information, and extramural infection is not required to be calculated. Therefore, the invention screens and divides the infection information H (b) Y based on the type field in the infection information, when the type field is in hospital, the infection record is in-hospital infection, and when the type field is out of hospital, the infection record is out-of-hospital infection.

Based on the above H (b) Y, H (c) Y is:

h (c) N is:

The normal time of infection should be within the patient's hospital stay, therefore, the present invention screens apparently erroneous data according to the parameter g.mc2. Specifically, the invention filters out the infection information H (d) N with the infection time not in the hospitalization period of the patient based on the comparison between the 'infection time' field in the infection information and the parameter g.MC2 of the hospitalization and discharge time, and obtains the infection information H (d) Y with the infection time in the hospitalization time range.

For H (c) _ Y above, H (d) _ Y, H (d) _ N is empty since H (c) _ Y is empty.

for the infection information H (d) Y, the invention firstly screens the infection information H (d) Y based on statistical time, authority departments and selected departments, and only if corresponding infection information exists after screening, the infection information H (g) Y belongs to the infection information of non-operation parts. The invention screens the infection information H (d) _ Y in turn based on the statistical time, the authority department and the selected department, therefore, the step S6 specifically comprises:

in order to obtain infection diagnosis information of contemporary infection, the invention firstly screens the infection information H (d) Y based on statistical time, and only if the infection time is within the range of statistical time period, the corresponding infection information is processed.

because the authority of each user is different, the invention screens the infection information H (e) Y based on the authority department, so that the data operated by the user is adaptive to the corresponding authority. Incidentally, the branch information h (f) _ Y is an infection record in a department belonging to the authority range managed by the user, and the branch information h (f) _ N is an infection record in a department not belonging to the authority range managed by the user.

S63, dividing the infection information H (f) Y into infection information H (g) Y of which the department belongs to the selected department and infection information H (g) N of which the department does not belong to the selected department based on the selected department, and taking the infection information H (g) Y as the infection information infected by the non-operation part;

in the invention, a user can check the infection omission of a new hospital aiming at a specific department, therefore, the invention screens the infection information H (f) Y based on the selected department, so that the statistical and screened data is adaptive to the department selected by the user independently, and the user can select the corresponding data as required to count the infection omission cases of the non-operation part of a specific department. Therefore, the infection information h (g) Y of the non-surgical site infection is finally generated.

For h (d) _ Y above, since h (d) _ Y is empty, h (e) _ Y, H (e) _ N, H (f) _ Y, H (f) _ N, H (g) _ Y, H (g) _ N is empty.

the operation information is used for recording the specific conditions of the operation performed by the patient, including the patient case number, the operating department, the operation name, the operation starting time, the operation ending time, the incision and the infection case identification. In order to solve the problem of operation record information of wrong time, the invention firstly screens the collected operation information G and selects the operation information G (a) _ Y which is performed within the time range of patient admission and discharge. Specifically, the invention filters out the operation information G (a) and N of the operation time which is not in the period of the patient in which the patient is in hospital based on the comparison between the field of 'operation start time' and 'operation end time' in the operation information and the parameter g.MC2 of the time of the patient in hospital, and obtains the operation information G (a) and Y which are performed in the time range of the patient in hospital and out hospital.

For example, the collected surgical information G is:

for g.MC2 above [ 2019-01-0100: 00:12,2019-01-1203: 00:12], the corresponding G (a) _ Y is:

g (a) _ N is:

for the operation information G (a) _ Y, the invention firstly screens the operation information G (a) _ Y based on the statistical time, the authority department and the selected department, and only if the corresponding operation information exists after screening, the operation information belongs to the operation information meeting the corresponding requirement limitation. The invention screens the operation information G (a) _ Y in turn based on the statistical time, the authority department and the selected department, therefore, the step S8 specifically comprises the following steps:

in connection with contemporary infection, the surgical site infection takes the surgical start time as the infection time, and the statistical contemporary infection information also requires the surgical start time to be within the statistical time range. Therefore, the present invention first filters the surgical information g (a) _ Y based on statistical time.

For G (a) Y and the statistical time [ 2019-01-0600: 00:00 to 2019-01-2023:59:59], G (b) Y is:

g (b) _ N is:

because the authority of each user is different, the invention screens the operation information G (b) _ Y based on the authority department, so that the data operated by the user is adaptive to the corresponding authority. Incidentally, the operation information g (c) _ Y is an operation record in a department belonging to the authority range managed by the user, and the operation information g (c) _ N is an operation record in a department not belonging to the authority range managed by the user.

If the authority department is all departments, g (b) _ Y is:

g (c) _ N is:

In the invention, the user can check the infection and omission of the new hospital aiming at a specific department, therefore, the invention screens the operation information G (c) Y based on the selected department, so that the statistical and screened data is adaptive to the department selected by the user independently, and the user can select the corresponding data according to the requirement. When the 'operating department' field in the operation information belongs to the selected department range, the operation information G (d) _ Y corresponding to the hospitalized department is obtained, and when the 'operating department' field in the operation information belongs to the selected department range, the operation information G (d) _ N not corresponding to the department is obtained.

When the selected department is ICU, G (d) Y is:

g (d) N is:

as described above, the operation information includes the infection case identification field, and the invention selects and obtains the g.8QR of the infection case related to the infection information according to the operation information G (d) _ Y. This section acquires an association condition for associating relationships between different types.

Further, the present invention obtains infection information H (b1) _ Y of surgical site infection for confirming infection information of surgical site infection based on infection information H (a) _ Y and infection case identification g.8qr. The remaining infection information is H (b1) _ N.

For the G (d) Y, the obtained infection example identifier g.8QR is GID 0001; for the above H (a) _ Y and infection case identifier g.8qr, H (b1) _ Y are:

h (b1) _ N is:

since the infection diagnostic information includes the infection information of the non-surgical site infection and the infection information of the surgical site infection, the present invention combines the obtained infection information H (g) _ Y of the non-surgical site infection and the obtained infection information H (b1) _ Y of the surgical site infection to obtain the infection diagnostic information H (H).

For H (g) r Y, H (b1) Y above, the combined H (h) is:

the invention is used for checking the leakage of new nosocomial infections, and the related infections need to be generated before discharge. Therefore, the present invention acquires the discharge time g.3cn in the hospitalization procedure information a, and takes this as the parameter g.3cn. This step is to sort out the discharge time of the patient's stay in the hospital as a quoted parameter. Convenient for repeated use at the back.

In order to ensure that the infection of the new nosocomial infection is in the hospital, the invention firstly screens the infection diagnosis information H (h) based on the discharge time g.3CN, and filters the infection diagnosis information H (i) Y generated before the discharge of the patient and the infection diagnosis information H (i) N generated after the discharge. Therefore, the method and the system filter out the infection cases which can not be reported by the clinician before the patient is discharged, and reduce the influence of confirmed infection cases after discharge on the calculation of missing report.

The hospital stay information a collected is:

The discharge time g.3CN is 2019-01-1203: 00: 12.

Based on the above H (h) and g.3CN, H (i) Y is:

h (i) _ N is:

The new cases of missed reports of nosocomial infections are infection diagnosis records which are reported by clinicians before patients are discharged, so the invention screens the infection diagnosis information H (i) _ Y, and particularly screens the infection diagnosis information H (i) _ Y based on the field of clinical report contents in the infection information. And when the field of the clinical report content is 'confirmation', the infection diagnosis record H (j) _ N confirmed by the clinician in time before the patient is discharged is obtained through filtering, and when the field of the clinical report content is not 'confirmation', the infection diagnosis record H (j) _ Y which is not reported and is required to be reported by the clinician before the patient is discharged is obtained through filtering. The infection diagnosis record H (j) _ Y obtained by the method is the record information related to the new hospital infection cases in the specific period. And outputting 0 if the infection diagnosis record of H (j) _ Y is empty, and outputting the corresponding hospital infection case times if the record is not empty. And outputting H (i) _ Y when the specific report missing record needs to be output.

Based on the above H (i) Y and g.3CN, H (j) Y is:

h (j) N is:

since H (j) _ Y is empty, i.e. there is no record in H (j) _ Y, the output number of missed hospital infections is 0.

Example two

As shown in fig. 2, the present embodiment provides an automatic leak detection system for newly-released hospital infection in a specific period, which includes:

The collection and judgment module is used for collecting the patient's branch information B, judging whether the branch information B has a branch record that the time is crossed with the statistical time and the departments belong to the authority department and the selected department at the same time, if so, calling the first collection module, and if not, outputting the number of missed hospital infection as 0;

the branch information is used for recording the information of entering and leaving the department of each diagnosis and treatment department during the hospitalization period of the patient, and specifically comprises the patient case number, the department, the time of entering the department, the time of leaving the department and the like. For the branch information B, the invention firstly screens the branch information based on statistical time, authority departments and selected departments, and the missed new hospital infection is possible to exist only if the corresponding branch records exist after screening. Therefore, when there is no branch record after screening, that is, there is no case of meeting the requirements of statistical time, authority department and selected department at the same time, the number of hospital infection missed reports is 0, that is, there is no case of missed reports of new hospital infection. The invention screens the branch information in sequence based on the statistical time, the authority department and the selected department, therefore, the acquisition and judgment module specifically comprises:

And the judging module is used for judging whether the branch information B (c) and Y (Y) has a branch record, if so, the first acquisition module is called, and if not, the number of the missed hospital infection is 0.

the invention screens the acquired infection information H (a) Y and selects the infection information which is irrelevant to the operation position, infected in a hospital and the infection time of the patient in the hospital, therefore, the infection information dividing module specifically comprises:

For H (c) _ Y above, H (d) _ Y, H (d) _ N is empty since H (c) _ Y is empty.

for the infection information H (d) Y, the invention firstly screens the infection information H (d) Y based on statistical time, authority departments and selected departments, and only if corresponding infection information exists after screening, the infection information H (g) Y belongs to the infection information of non-operation parts. The invention screens the infection information H (d) Y in turn based on the statistical time, the authority department and the selected department, therefore, the non-operation part infection information determining module specifically comprises:

An infection information seventh dividing module for dividing the infection information h (f) _ Y into infection information h (g) _ Y in which the department belongs to the selected department and infection information h (g) _ N in which the department does not belong to the selected department, based on the selected department, the infection information h (g) _ Y being infection information for a non-surgical site;

for the operation information G (a) _ Y, the invention firstly screens the operation information G (a) _ Y based on the statistical time, the authority department and the selected department, and only if the corresponding operation information exists after screening, the operation information belongs to the operation information meeting the corresponding requirement limitation. The invention screens the operation information G (a) _ Y in turn based on the statistical time, the authority department and the selected department, therefore, the operation information dividing module specifically comprises:

Therefore, the method and the system for automatically checking the new hospital infection at the specific time interval record the specific implementation mode of automatically checking the hospital infection in detail, and the method and the system can automatically check the new hospital infection at the specific time interval by utilizing the information of the department transfer, the information of the hospitalization process, the infection information, the operation information, the selected statistical time, the department and the authority department of the user according to the identity information of the user, and can automatically acquire and output the hospital infection number which is missed to be reported; hospital infection can be automatically checked, the labor intensity of manual data statistics is avoided, and automatic supervision of hospital infection information is realized by automatically checking new hospital infection; the method has the advantages that the method can effectively distinguish the hospitalization period from the hospitalization period of the sensing diseases, can accurately search the new reported cases of the hospital, simultaneously fully utilizes the information of the department transfer, the hospitalization process, the infection information and the operation information, finely analyzes the relevant data of the infection information, accurately determines the new reported cases of the hospital infection, and has high leak detection accuracy.

It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for automatically detecting new hospital infections at a specific time interval, comprising the steps of:

2. The method for automatically detecting leaks according to claim 1, wherein the step S2 specifically comprises:

3. The method for automatically detecting leaks according to claim 1, wherein the step S5 specifically comprises:

4. The method for automatically detecting leaks according to claim 1, wherein the step S6 specifically comprises:

5. The method for automatically detecting leaks according to claim 1, wherein the step S8 specifically comprises:

6. A system for automatic leak detection of newly-developed nosocomial infections at specified time intervals, comprising:

the first infection information dividing module is used for collecting infection information H of a patient, and dividing the infection information H into infection information H (a) Y confirmed by a user and infection information H (a) N not confirmed by examination; an infection information partitioning module for obtaining infection information of the infection information h (a) Y that is surgical site-independent, infected in a hospital and has an infection time during hospitalization of a patient, based on the parameter g.mc2;

7. The system of claim 6, wherein the collecting and determining module comprises:

8. The system for automatically detecting leaks according to claim 6, wherein the infection information partitioning module specifically comprises:

9. The system for automatically detecting leaks of claim 6, wherein the non-surgical site infection information determination module specifically comprises:

10. The system for automatically detecting leaks of claim 6, wherein the surgical information partitioning module specifically comprises: